Transcript LMI Basics 1 - WorkForceInfoDB

Welcome
Please sit wherever
you would like
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Word on the street is
you been askin’ a lotta
questions about LMI…
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LMI.. What you should know
Presented by….
Bill McNeece
MS Dept of Employment Security
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LMI
What is it?
Where does it come
from?
How can you use it?
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One Popular Opinion
L
Made Up
I nformation
argely
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But, seriously, folks …
L
M
I
abor
arket
nformation
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The Textbook Definition
A dynamic and systematic
approach to workforce data —
designed to meet the changing
needs of our customers.
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In Layman’s Terms
Or, to put it more simply …
Basically, it’s any data or analysis that
relates to the workforce.
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LMI ????????????
Unfortunately,
you do
LMI data is the gas that fuels the
ALMIS Data Base engine
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What’s our goal today?
To help YOU….
 Navigate thru the LMI Lingo
 Understand the Data Sources
Avoid Heartburn and Keep Your
Sanity
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Your Training Modules Today:
 Learning the Lingo
 Who Makes this Stuff Up?
 Avoiding Heartburn
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Ready to get started?
Let’s take a look at the first module
the
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Feel Bombarded with Acronyms?
Americans DO love their
acronyms!
But sometimes it makes things hard
to understand
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Did you know?
Acronym is actually an ACRONYM itself!
Abbreviations
Created
Routinely
Once every
New
York
Minute
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Before we get very far
We need to wade through some
Alphabet Soup so you won’t think
I’m speaking a foreign language
These are some common
acronyms tossed around in LMI
circles
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Alphabet Soup
BEA = Bureau of Economic Analysis
BLS = Bureau of Labor Statistics
CPI = Consumer Price Index
CES = Current Employment Statistics
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Alphabet Soup
CPS = Current Population Survey
ECI = Employer Cost Index
ETA = Employment & Training Administration
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Alphabet Soup
LAUS = Local Area Unemployment Statistics
LMA = Labor Market Area
MLS= Mass Layoff Statistics
MSA = Metropolitan Statistical Area
NAICS = North American Industry
Classification System
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Alphabet Soup
OES= Occupational Employment Statistics
PPI = Producers Price Index
SIC = Standard Industry Classification
SOC = Standard Occupational Classification
QCEW = Quarterly Census of Employment &
Wages
(a.k.a ES 202)
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Alphabet Soup
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LMI Lingo
Must crawl before we walk
We’ll start with some basic
terms and concepts
In other words, all you wanted
to know but were afraid to ask
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Labor Force Terms & Concepts
Employed
Worked at least one hour for pay
During the week that includes the 12th
Unemployed
No job attachment
Available for work & actively
seeking it
Can be experienced or
a new or re-entrant
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Covered Employment
This employment tallies workers whose
wages have been “covered” for UI
purposes (i.e., the employer paid
unemployment insurance on the
wages paid to the individual)
Used only in QCEW data
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Employment
Place of work
An estimate or count of employment based
on the location of the job regardless of the
worker’s residence
Also called Nonag Wage and Salary or
Nonfarm Employment
This counts jobs, not people
Used in QCEW, OES and CES data
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Employment
Place of Residence
An estimate of employment based on where
the employee lives, rather than where they
work
This is a count of people not jobs
Used in calculating the labor force
Used only in LAUS data
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Labor Force Terms & Concepts
 Civilian Labor Force
 16+ years old
 Employed + Unemployed
 Does NOT include military personnel
Unemployment rate
Unemployed ÷ Labor Force
Expressed as %
Labor Force Participation rate
Labor Force ÷ Working Age Population
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Labor Force Terms & Concepts
 Labor Market Area
Groups of counties
that encompass the
county of residence
and the county of
work.
Defined by:
 Commuting patterns
 The behavior of
individuals included
in American
Community Survey,
Census and UI claims
data when compared
to other data.
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Covered Wages
This pertains to the actual wages
earned by persons working for a
“covered” employer
In other words, someone for whom
unemployment tax has been paid
Used only in QCEW data
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Benchmark
Establishing a new reference
point, from which estimates
are calculated and/or revised,
based on last known data.
Very similar to the census
process
Only LAUS & CES do this
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Coding Systems
Why code data?
Why revise
coding
structures?
Types of
coding:
Geography
Industry
Occupation
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Objectives of Coding Systems
 Often designed to meet
specific labor program
needs
 Ideally, a single system
would meet all
programmatic needs
 Updating should be
timely and cost-effective
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Geographic Coding Systems
 Only one major system in common usage:
FIPS – Federal Information Processing System
Developed by U.S. Office of Management and Budget
(OMB)
Commonly used by almost all federal and local
agencies
Consists of codes for states, MSA’s, counties and
cities, townships, etc.
Some GIS software applications use FIPS
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Industry Coding Systems
Types:
Standard Industrial
Classification (SIC)
North American
Industrial
Classification System Shifting from SIC to
NAICS
(NAICS)
Conversion now
complete
Benefits
Program impacts
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WHY NAICS?
 Six-digit system, instead of four
 Instead of 10 major industry groups, there are
20 industrial sectors.
 More consistent with other international
systems and other classification systems used
by BEA.
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Occupational Coding Systems
DOT — Dictionary of Occupational Titles
 Phased out in 2002 – 2003
OES — Occupational Employment Statistics
SOC — Standard Occupational Code
O*NET — Occupational Information Network
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LMI Lingo
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Next on our agenda is…
Who makes
this stuff
up?
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Just where do the numbers come from?
Mostly from BLS
programs
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Just who or what IS BLS?
Contrary to popular
opinion, they are NOT
the Bureau of Lying
Sapsuckers!
In reality, they are the
BUREAU OF LABOR
STATISTICS, an arm of
the US Department of
Labor
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As states, why are we involved
with a Federal agency?
They operate what
is known as the
Federal/State
Cooperative
Programs
Under these, they
provide the funding
for our base
statistical programs
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Historical Background
BLS has been
around in one form
or another for over a
hundred years.
However, they only
took control over the
LMI programs in the
mid-1970’s
They provide both
funding and
technical support
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LMI Produces lots of different
stuff
Does BLS control
ALL our LMI
programs?
Not in most states.
They are only
responsible for FIVE
basic statistical
programs. Anything
else is funded and
controlled by some
other entity
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Which five does BLS
control?





QCEW
CES
LAUS
OES
MLS
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There you go with the
acronyms again!
In plain English, tell
me what those
stand for
And while you’re at
it, tell me a little
bit about each of
them
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Okay, let’s begin with QCEW
It’s official name is the
Quarterly Census of
Employment & Wages
It’s commonly called
ES 202 because the
original report it was
required to produce
was Employment
Security Report
Number 202
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What exactly does the QCEW
program produce?
Detailed quarterly
employment and
payroll information for
all employers covered
under UI law.
Annual information on
changes in industry
codes that occur
during the year
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Data Sources for QCEW
UI quarterly
contribution reports
UCFE federal
agency employment
reports
Comes to ALMIS DB
via EQUI report
Supplementary
employer surveys by
state LMI offices
Multiple establishment
detail (MWR)
Industrial coding
(annual refile survey)
Follow-ups triggered
by edits
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How does QCEW
differ from other programs?
Unlike LAUS, QCEW
counts JOBS not
PEOPLE
Jobs are counted at
the work site
It’s the only program
that lists total wages
paid
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Uses of QCEW Data
 Employment
benchmark for all
BLS federal/state
employer survey
programs — CES,
OES & OSHA
Critical for Bureau of
Economic Analysis
Personal income
State and national
domestic product
Local planning
Only consistent
source of county
employment and
wages by industry
Any employment
analysis requiring
detailed data
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QCEW Limitations & Changes
 Some employment for large firms may be
reported in the wrong areas (MWR’s)
 Some firms report total number of employees
in a quarter as employment for each month
 QCEW is not a time series
No wedging of changes by industry or area
from:
Annual refile survey
Changes in multi-establishment reporting
 Shift to NAICS — Break in series
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QCEW Chronology
Data files produced QUARTERLY
Once completed they are NOT
revised
Changes in industry designation
only done ANNUALLY
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QCEW
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Next on the agenda …
Which stands for: Current Employment Statistics
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What is it?
 The Current Employment
Statistics program is a
monthly employer survey
conducted by the states
in cooperation with BLS.
 The survey provides a
sample from which
estimates of
employment, hours and
earnings by industry
group are calculated
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What does it produce?
 Today, the CES
program produces
employment, hours
and earnings estimates
for all states and
MSA’s.
 It is the largest survey
of its kind, with a
nationwide sample of
over 400,000 firms!
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Coverage Differences Between
CES & QCEW
The following categories of workers are
included in CES estimates but not in
QCEW
Full commission salespersons
Elected and appointed government officials
Teachers in summer months who are paid
on 12-month contracts
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CES Limitations & Changes
 Sample size limits state & area industry detail
 Sum of states’ employment does not equal national
total
 Estimates for many sub-state areas are not funded
 Though accuracy exceeds that of other economic
data, benchmark revisions still cause criticism
 Earnings are for production workers & not available
for many state industries
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CES Chronology
 Data produced MONTHLY
 Current month is PRELIMINARY, previous month is
REVISED
 Entire calendar year data set is benchmarked and
revised ANNUALLY
 Benchmark revisions include prior year, also
 Hours and earnings data are revised monthly but
NOT BENCHMARKED
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Current Employment Statistics
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Moving right along …
We come to
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Occupational Employment
Statistics (OES)
 An annual employer survey which produces
employment and wage-rate estimates by
occupation and industry for states and areas
 Program began in 1971 in 15 states with BLS
and ETA sharing responsibility with the states
 When BLS took total federal responsibility for
the program, all 50 states began to participate
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OES
In 1996, the following changes were
made:
Sample increased to be the largest of any
employer survey
Wage rates were added for all states & substate areas
All industries surveyed each year, rather
than every 3rd year
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OES Staffing Estimates
Employment by
occupation is
tallied for each
industry sector
Staffing ratios are
developed
representing each
occupation’s share of
each industry
sector’s employment
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OES Wage Rate Estimates
Data tallied by wage ranges
Wage-rate averages
generated using weighted
system of averaging
Prior-year data “aged” using
the Employer Cost Index
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OES Limitations
 Since it is voluntary, low response rates can
make it less reliable in some industry sectors
 Estimates for sub-state areas dependent on
sample size and response rates
 Wages are tallied by range
 Sample size limits state & area industry
detail in many cases
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Occupational Employment Statistics
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State and Area Occupational
Projections
A very important byproduct of the
OES data
NOT a BLS funded project
Money comes from Employment &
Training Administration…another
branch of the US Department of
Labor
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State & Area Occupational
Projections
Produces both the
INDPRJ and
In some states unit may
IOMATRIX data sets
also be responsible for
Short-term —
occupational wage data
up to 2 years
Substate areas vary
Long-term —
widely from state to state
roughly 10 years
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Projections
Chronology
New data sets now
released twice a
Release times vary
year
widely from state to
Short term and
state
long term
Data are not subject
projections not
to benchmark
necessarily
revisions
released at same
time
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The fourth BLS program is
which stands for
Local Area Unemployment Statistics
________________________________
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Just what is LAUS?
The name can be
misleading since
it deals with
more than just
unemployment
data, such as the
often-quoted
unemployment
rate.
The Local Area
Unemployment
Statistics program
is a multi-layered
process that
produces labor
force, employed
and unemployed
estimates by
place of residence
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What does the LAUS program
produce?
Estimates of total
civilian labor force,
employed,
unemployed and
unemployment rate
for all states, MSA’s,
counties, and other
similar areas,
adjusted to place of
residence
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Betcha didn’t know…
Estimation method varies depending on the
type of geography
U.S. data comes directly from the monthly
Current Population Survey
Statewide data (since 1986) comes from a
regression model developed by BLS
County level data are apportioned out of the
statewide data using a handbook method
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Why do methods vary?
CPS allows for more detailed information
at the national level, such as data by
gender, race, age group, etc.
CPS was used for larger states at one
time, but trend was erratic and regression
model was instituted in late 1980’s
Regression models are not reliable for
smaller areas, such as counties and cities
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Sub-state LAUS Estimates
Handbook method used to apportion out
county level estimates from statewide
totals
Population-claims method used where
possible for estimates of larger cities
Census-share method used for smaller
cities and sub-county estimates when
claims data are not available
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How do LAUS estimates differ
from others?
 Includes agricultural
workers, self employed
and others excluded by
CES & QCEW
 CES & QCEW estimate
JOBS at work site;
LAUS estimates PEOPLE
at place of residence
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LAUS Limitations
 Limited statistical measures of reliability
 Handbook methodology assumes local
areas follow national trends
 Estimates for employment are probably
more accurate than for unemployment
 No detailed data, such as gender, age, etc.
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LAUS Chronology
 Data produced monthly
 Current month is PRELIMINARY, previous
month is REVISED
 Entire calendar year data set is
benchmarked and revised ANNUALLY
 Benchmark revisions may include prior
years, also
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Local Area Unemployment
Statistics
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Last
(but not necessarily least)
we come to
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Mass Layoff Statistics
Began life as PMLPC in the early 80’s
Intent was to track serious layoffs and
closings by industry using UI claims data
Not very useful for Rapid Response
Good post-occurrence analytical tool
Many states don’t have enough activity
to publish data
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BLS Programs
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Okay…..That covers the
BLS generated stuff…..
What about all the other data
sets in the ALMIS DB?
“Other” data sets
 Occupational licensing data – Sources
vary by state
 Census data (www.census.gov)
 Most can be downloaded in Excel format
 State data center can be helpful
 Training provider and completer data –
Sources vary by state
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“Other” data sets
Income data – downloadable from BEA
web site.
Crosswalk tables – Direct from National
Crosswalk Data Center in Iowa
Employer database – provided via
contract with InfoUSA – updates
automatic
URL links to other states
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Okay… I dig the data now, but how
do I keep it all straight without
going postal and doing something
crazy?
Fair question...
and it leads to our last module…..
Top Three Tips
1) Get a handle on Benchmarking
procedures
2) Understand the data flow
3) Understand the BLS vs ETA
issues
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To elaborate...
 Know the timing of data sets
from BLS
 Know who provides, when and
in what format
 Don’t be blind-sided by
revisions
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Benchmarking
 Know the time frame for
benchmarking for CES and
LAUS
 Understand the scope
 Double check data to insure it
is the most current benchmark
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BLS vs ETA
 Realize they don’t like each
other very much
 Understand the ‘turf wars’
 Don’t expect them to cooperate
and make your life easier
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Almost done
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Th-th-th-that’s all folks!
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Applause !!
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For further assistance contact:
Bill McNeece – Special Projects
LMI Department - MS Department of
Employment Security
Phone: 601 321 6249
E-mail: [email protected]
NO EXTRA CHARGE !!